

Building your pipeline or Using Airbyte
Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes



Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
Simple & Easy to use Interface
Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.
Guided Tour: Assisting you in building connections
Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.
Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes
Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.
What sets Airbyte Apart
Modern GenAI Workflows
Move Large Volumes, Fast
An Extensible Open-Source Standard
Full Control & Security
Fully Featured & Integrated
Enterprise Support with SLAs
What our users say

Andre Exner

"For TUI Musement, Airbyte cut development time in half and enabled dynamic customer experiences."

Chase Zieman

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Rupak Patel
"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."
Begin by familiarizing yourself with Yotpo's API documentation. Identify the endpoints that provide the data you need. Yotpo typically offers RESTful APIs that require authentication, usually via API keys. Ensure you have the necessary permissions and API keys to access the data.
Prepare your development environment by installing the necessary tools and libraries. You will likely need a programming language that can handle HTTP requests, such as Python, Node.js, or Ruby. Ensure you have a Redis client library for your chosen language to interact with the Redis database.
Write a script to authenticate with Yotpo's API using your API key. Construct HTTP GET requests to the relevant endpoints to fetch the data you need. Store the API responses locally, ensuring that you handle pagination if the data is extensive.
Once you have the data from Yotpo, process it to fit the structure required by Redis. This may involve transforming JSON responses into key-value pairs or other data structures that Redis supports, such as hashes or lists. Ensure that the data is cleaned and formatted correctly to avoid errors during insertion.
Use the Redis client library to establish a connection to your Redis database. Ensure that your Redis server is running and accessible. Configure the connection settings, such as the host, port, and authentication credentials if required.
With the connection established, write a script to insert the processed data into Redis. Use appropriate Redis commands to store the data. For example, use `SET` for simple key-value pairs, `HSET` for hashes, and `LPUSH` for lists. Ensure that you handle any potential errors that may arise during this process.
After data insertion, verify that the data in Redis accurately reflects the data fetched from Yotpo. Perform checks to ensure data integrity. Once verified, consider automating the data migration process using cron jobs or another scheduling method to keep your Redis database updated with the latest data from Yotpo.
By following these steps, you can effectively move data from Yotpo to Redis without relying on third-party connectors or integrations.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Yotpo is a customer content marketing platform that helps businesses generate and leverage customer reviews, photos, and Q&A to increase sales and build brand loyalty. The platform offers a suite of tools that enable businesses to collect and showcase user-generated content across various channels, including their website, social media, and email marketing campaigns. Yotpo also provides advanced analytics and insights to help businesses understand their customers' behavior and preferences, as well as tools to engage with customers and respond to their feedback. Overall, Yotpo helps businesses create a more authentic and engaging customer experience that drives growth and customer loyalty.
Yotpo's API provides access to a wide range of data related to customer reviews, ratings, and user-generated content. The following are the categories of data that can be accessed through Yotpo's API:
1. Reviews and Ratings: Yotpo's API provides access to all customer reviews and ratings for a particular product or service.
2. User-Generated Content: Yotpo's API allows access to user-generated content such as photos, videos, and social media posts related to a particular product or service.
3. Customer Data: Yotpo's API provides access to customer data such as name, email address, and location.
4. Analytics: Yotpo's API allows access to analytics data such as conversion rates, click-through rates, and engagement metrics.
5. Product Data: Yotpo's API provides access to product data such as product descriptions, pricing, and inventory levels.
6. Order Data: Yotpo's API allows access to order data such as order status, shipping information, and payment details.
7. Marketing Data: Yotpo's API provides access to marketing data such as campaign performance, email open rates, and click-through rates.
Overall, Yotpo's API provides a comprehensive set of data that can be used to gain insights into customer behavior, improve product offerings, and optimize marketing strategies.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: